Which industries are ahead in agentic AI, and the common challenge they all face
A Teradata survey finds only 7% of organizations have reached the operationalizing stage as fragmented data and weak context limit AI agents.
- Teradata released "Arrested Automation: Why Agentic AI Stalls at the Enterprise Level" on Tuesday, revealing that data fragmentation prevents organizations from scaling agentic AI reliably across enterprises.
- According to the Agentic AI Maturity Index, only 7% of organizations have reached the operationalizing stage, while 40% remain in the developing phase, unable to build the enterprise context necessary for autonomous decision-making.
- Manufacturing leaders see agentic AI as a competitive opportunity, yet only 8% have operationalized it, with 54% citing legacy system disconnects; healthcare leaders report that 90% of their organizations have 20% or less sufficiently contextualized data.
- Retailers rely heavily on satisfaction metrics, but data fragmentation keeps only 5% at the operationalizing stage; banks prioritize enterprise-wide ROI yet report that 50% face governance restrictions limiting agent data access.
- To unlock organizational ROI, companies must prioritize building a robust data foundation enriched with business-level metadata, as the biggest roadblock all organizations face is fundamental data and context fragmentation.
43 Articles
43 Articles
Which industries are ahead in agentic AI, and the common challenge they all face - The Mexico Ledger
Which industries are ahead in agentic AI, and the common challenge they all faceSome industries are moving faster than others to deploy agentic AI, but a new report from autonomous AI knowledge platform company Teradata suggests they are all running into a version of the same problem: Their data is too fragmented, sensitive or disconnected and lacks critical context for AI agents to act on reliably at scale.The findings show healthcare, manufact…
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Which industries are ahead in agentic AI, and the common challenge they all face
Teradata reports that various industries are advancing in agentic AI but face common challenges, particularly data fragmentation and regulatory constraints.
Which industries are ahead in agentic AI, and the common challenge they all face - Stateline Publications
Which industries are ahead in agentic AI, and the common challenge they all faceSome industries are moving faster than others to deploy agentic AI, but a new report from autonomous AI knowledge platform company Teradata suggests they are all running into a version of the same problem: Their data is too fragmented, sensitive or disconnected and lacks critical context for AI agents to act on reliably at scale.The findings show healthcare, manufact…
Which industries are ahead in agentic AI, and the common challenge they all face - Hillsboro Sentry Enterprise
Which industries are ahead in agentic AI, and the common challenge they all faceSome industries are moving faster than others to deploy agentic AI, but a new report from autonomous AI knowledge platform company Teradata suggests they are all running into a version of the same problem: Their data is too fragmented, sensitive or disconnected and lacks critical context for AI agents to act on reliably at scale.The findings show healthcare, manufact…
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